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I am making a script, that should create a schema for each customer. I’m fetching all metadata from a database that defines how each customer’s schema should look like, and then create it. Everything is well defined, the types, names of tables, etc. A customer has many tables (fx, address, customers, contact, item, etc), and each table has the same metadata.
My procedure now:
get everything I need from the metadataDatabase.
In a for loop, create a table, and then Alter Table and add each metadata (This is done for each table).
Right now my script runs in about a minute for each customer, which I think is too slow. It has something to do with me having a loop, and in that loop, I’m altering each table.
I think that instead of me altering (which might be not so clever approach), I should do something like the following:
Note that this is just a stupid but valid example:
for table in tables:
con.execute("CREATE TABLE IF NOT EXISTS tester.%s (%s, %s);", (table, "last_seen date", "valid_from timestamp"))
But it gives me this error (it seems like it reads the table name as a string in a string..):
psycopg2.errors.SyntaxError: syntax error at or near "'billing'"
LINE 1: CREATE TABLE IF NOT EXISTS tester.'billing' ('last_seen da...
Consider creating tables with a serial type (i.e., autonumber) ID field and then use alter table for all other fields by using a combination of sql.Identifier for identifiers (schema names, table names, column names, function names, etc.) and regular format for data types which are not literals in SQL statement.
from psycopg2 import sql
# CREATE TABLE
query = """CREATE TABLE IF NOT EXISTS {shm}.{tbl} (ID serial)"""
cur.execute(sql.SQL(query).format(shm = sql.Identifier("tester"),
tbl = sql.Identifier("table")))
# ALTER TABLE
items = [("last_seen", "date"), ("valid_from", "timestamp")]
query = """ALTER TABLE {shm}.{tbl} ADD COLUMN {col} {typ}"""
for item in items:
# KEEP IDENTIFIER PLACEHOLDERS
final_query = query.format(shm="{shm}", tbl="{tbl}", col="{col}", typ=i[1])
cur.execute(sql.SQL(final_query).format(shm = sql.Identifier("tester"),
tbl = sql.Identifier("table"),
col = sql.Identifier(item[0]))
Alternatively, use str.join with list comprehension for one CREATE TABLE:
query = """CREATE TABLE IF NOT EXISTS {shm}.{tbl} (
"id" serial,
{vals}
)"""
items = [("last_seen", "date"), ("valid_from", "timestamp")]
val = ",\n ".join(["{{}} {typ}".format(typ=i[1]) for i in items])
# KEEP IDENTIFIER PLACEHOLDERS
pre_query = query.format(shm="{shm}", tbl="{tbl}", vals=val)
final_query = sql.SQL(pre_query).format(*[sql.Identifier(i[0]) for i in items],
shm = sql.Identifier("tester"),
tbl = sql.Identifier("table"))
cur.execute(final_query)
SQL (sent to database)
CREATE TABLE IF NOT EXISTS "tester"."table" (
"id" serial,
"last_seen" date,
"valid_from" timestamp
)
However, this becomes heavy as there are too many server roundtrips.
How many tables with how many columns are you creating that this is slow? Could you ssh to a machine closer to your server and run the python there?
I don't get that error. Rather, I get an SQL syntax error. A values list is for conveying data. But ALTER TABLE is not about data, it is about metadata. You can't use a values list there. You need the names of the columns and types in double quotes (or no quotes) rather than single quotes. And you can't have a comma between name and type. And you can't have parentheses around each pair. And each pair needs to be introduced with "ADD", you can't have it just once. You are using the wrong tool for the job. execute_batch is almost the right tool, except it will use single quotes rather than double quotes around the identifiers. Perhaps you could add a flag to it tell it to use quote_ident.
Not only is execute_values the wrong tool for the job, but I think python in general might be as well. Why not just load from a .sql file?
I am trying to write a general function that will insert a line of data into a table in a database but I am trying to write an array of unknown length. I am aiming to just be able to call this function in any programand write a line of data of any length to the table (assuming the table and the array are the same length.
I have tried adding the array like it is a singular peice of data.
import sqlite3
def add2Db(dbName, tableName, data):
connection = sqlite3.connect(dbName)
cur = connection.cursor()
cur.execute("INSERT INTO "+ tableName +" VALUES (?)", (data))
connection.commit()
connection.close()
add2Db("items.db", "allItems", (1, "chair", 5, 4))
This just crashes and gives me an error saying it has 4 columns but only one value was supplied.
SQLite does not support arrays - you have to convert to a TEXT using ','.join() to join your array items into a single string and pass that.
Source: SQLite website
https://www.sqlite.org/datatype3.html
I'm not a Python programmer, but I've been doing SQL a long time. I even wrote my own ORM. My advice is do not write your own SQL query builder. There's a myriad of subtle issues and especially security issues. I elaborate on a few of them below.
Instead, use a well-established SQL Query Builder or ORM. They've already dealt with these issues. Here's an example using SQLAlchemy.
from datetime import date
from sqlalchemy import create_engine, MetaData
# Connect to the database with debugging on.
engine = create_engine('sqlite:///test.sqlite', echo=True)
conn = engine.connect()
# Read the schemas from the database
meta = MetaData()
meta.reflect(bind=engine)
# INSERT INTO users (name, birthday, state, country) VALUES (?, ?, ?, ?)
users = meta.tables['users']
conn.execute(
users.insert().values(name="Yarrow Hock", birthday=date(1977, 1, 23), state="NY", country="US")
)
SQLAlchemy can do the entire range of SQL operations and will work with different SQL variants. You also get type safety.
conn.execute(
users.insert().values(name="Yarrow Hock", birthday="in the past", state="NY", country="US")
)
sqlalchemy.exc.StatementError: (exceptions.TypeError) SQLite Date type only accepts Python date objects as input. [SQL: u'INSERT INTO users (name, birthday, state, country) VALUES (?, ?, ?, ?)']
insert into table values (...) relies on column definition order
This relies on the order columns were defined in the schema. This leaves two problems. First is a readability problem.
add2Db(db, 'some_table', (1, 39, 99, 45, 'papa foxtrot', 0, 42, 0, 6)
What does any of that mean? A reader can't tell. They have to go digging into the schema and count columns to figure out what each value means.
Second is a maintenance problem. If, for any reason, the schema is altered and the column order is not exactly the same, this can lead to some extremely difficult to find bugs. For example...
create table users ( name text, birthday date, state text, country text );
vs
create table users ( name text, birthday date, country text, state text );
add2Db(db, 'users', ('Yarrow Hock', date(1977, 1, 23), 'NY', 'US'));
That insert will silently "work" with either column order.
You can fix this by passing in a dictionary and using the keys for column names.
add2Db(db, 'users', (name="Yarrow Hock", birthday=date(1977, 1, 23), state="NY", country="US"));
Then we'd produce a query like:
insert into users
(name, birthday, state, country)
values (?, ?, ?, ?)
This leads to the next and much bigger problem.
SQL Injection Attack
Now this opens up a new problem. If we simply stick the table and column names into the query that leaves us open to one of the most common security holes, a SQL Injection Attack. That's where someone can craft a value which when naively used in a SQL statement causes the query to do something else. Like Little Bobby Tables.
While the ? protects against SQL Injection for values, it's still possible to inject via the column names. There's no guarantee the column names can be trusted. Maybe they came from the parameters of a web form?
Protecting table and column names is complicated and easy to get wrong.
The more SQL you write the more likely you're vulnerable to an injection attack.
You have to write code for everything else.
Ok, you've done insert. Now update? select? Don't forget about subqueries, group by, unions, joins...
If you want to write a SQL query builder, cool! If, instead, you have a job to do using SQL, writing yet another SQL query builder is not your job.
It's harder for anyone else to understand.
There's a good chance that any given Python programmer knows how SQLAlchemy works, and there's plenty of tutorials and documentation if they don't. There's no chance they know about your home-rolled SQL functions, and you have to write all the tutorials and docs.
You shouldn't try to write your own ORMs without an argumented need. You will have a lot of problems, for example here's quick 25 reasons not to.
Instead use any popular orm that is proven. I recommend using SQLAlchemy as a go to outside of Django. Using it you can map a dict of values to insert it into a model just like insert(schema_name).values(**dict_name) (here's an example of insert/update).
Change your function to this:
def add2Db(dbName, tableName, data):
num_qs = len(data)
qm = ','.join(list('?' * num_qs))
query = """
INSERT INTO {table}
VALUES ({qms})
""".format(table=tableName,
qms=qm)
connection = sqlite3.connect(dbName)
cur = connection.cursor()
cur.execute(query, data)
connection.commit()
connection.close()
I'm using plugin DataStax Python Driver for Apache Cassandra.
I want to read 100 rows from database and then insert them again into database after changing one value. I do not want to miss previous records.
I know how to get my rows:
rows = session.execute('SELECT * FROM columnfamily LIMIT 100;')
for myrecord in rows:
print(myrecord.timestamp)
I know how to insert new rows into database:
stmt = session.prepare('''
INSERT INTO columnfamily (rowkey, qualifier, info, act_date, log_time)
VALUES (, ?, ?, ?, ?)
IF NOT EXISTS
''')
results = session.execute(stmt, [arg1, arg2, ...])
My problems are that:
I do not know how to change only one value in a row.
I don't know how to insert rows into database without using CQL. My columnfamily has more than 150 columns and writing all their names in query does not seem as a best idea.
To conclude:
Is there a way to get rows, modify one value from every one of them and then insert this rows into database without using only CQL?
First, you need to select only needed columns from Cassandra - it will be faster to transfer the data. You need to include all columns of primary key + column that you want to change.
After you get the data, you can use UPDATE command to update only necessary column (example from documentation):
UPDATE cycling.cyclist_name
SET comments ='='Rides hard, gets along with others, a real winner'
WHERE id = fb372533-eb95-4bb4-8685-6ef61e994caa
You can also use prepared statement to make it more performant...
But be careful - the UPDATE & INSERT in CQL are really UPSERTs, so if you change columns that are part of primary key, then it will create new entry...
Let's say I have cassandra table define like this:
CREATE TABLE IF NOT EXISTS {} (
user_id bigint ,
username text,
age int,
PRIMARY KEY (user_id)
);
I have 3 list of same size let's 1 000 000 records in each list. Is it a good practice to insert data using a for loop like this:
for index, user_id in enumerate(user_ids):
query = "INSERT INTO TABLE (user_id, username, age) VALUES ({0}, '{1}', {1});".format(user_id, username[index] ,age[index])
session.execute(query)
Prepared statements with concurrent execution will be your best bet. The driver provides utility functions for concurrent execution of statements with sequences of parameters, just as you have with your lists: execute_concurrent_with_args
Zipping your lists together will produce a sequence of parameter tuples suitable for input to that function.
Something like this:
prepared = session.prepare("INSERT INTO table (user_id, username, age) VALUES (?, ?, ?)")
execute_concurrent_with_args(session, prepared, zip(user_ids, username, age))
Its probably a good idea to start by looking at the python driver getting started guide. If you have already seen that then apologies but I thought it worth mentioning.
Generally speaking you'd create your session object and then do your inserts inside your loop, probably using something like a prepared statement (talked about further down the getting started page) but also here and here
The example of the above page uses this as a good starting point
user_lookup_stmt = session.prepare("SELECT * FROM users WHERE user_id=?")
users = []
for user_id in user_ids_to_query:
user = session.execute(user_lookup_stmt, [user_id])
users.append(user)
You may also find this blog helps when talking about better throughput with the python driver
You might find the python driver github page a useful resource, in particular I found this example using a prepared statement here that might help you too.
I'm looking for some help on how to do this in Python using sqlite3
Basically I have a process which downloads a DB (temp) and then needs to insert it's records into a 2nd identical DB (the main db).. and at the same time ignore/bypass any possible duplicate key errors
I was thinking of two scenarios but am unsure how to best do this in Python
Option 1:
create 2 connections and cursor objects, 1 to each DB
select from DB 1 eg:
dbcur.executemany('SELECT * from table1')
rows = dbcur.fetchall()
insert them into DB 2:
dbcur.execute('INSERT INTO table1 VALUES (:column1, :column2)', rows)
dbcon.commit()
This of course does not work as I'm not sure how to do it properly :)
Option 2 (which I would prefer, but not sure how to do):
SELECT and INSERT in 1 statement
Also, I have 4 tables within the DB's each with varying columns, can I skip naming the columns on the INSERT statement?
As far as the duplicate keys go, I have read I can use 'ON DUPLICATE KEY' to handle
eg.
INSERT INTO table1 VALUES (:column1, :column2) ON DUPLICATE KEY UPDATE set column1=column1
You can ATTACH two databases to the same connection with code like this:
import sqlite3
connection = sqlite3.connect('/path/to/temp.sqlite')
cursor=connection.cursor()
cursor.execute('ATTACH "/path/to/main.sqlite" AS master')
There is no ON DUPLICATE KEY syntax in sqlite as there is in MySQL. This SO question contains alternatives.
So to do the bulk insert in one sql statement, you could use something like
cursor.execute('INSERT OR REPLACE INTO master.table1 SELECT * FROM table1')
See this page for information about REPLACE and other ON CONFLICT options.
The code for option 1 looks correct.
If you need filtering to bypass duplicate keys, do the insert into a temporary table and then use SQL commands to eliminate duplicates and merge them into the target table.